The magic of automatic reporting ✨

Rhian Davies

Meet Maria

Public Health analyst
Delivers monthly reports on NHS Workforce statistics
Uses Excel to analyse data
Uses Word to write branded reports

Cartoon of a woman smiling

Monthly Reports

Monthly Reports

Cartoon of a spreadsheet, then a woman coding.

Monthly Reports

Cartoon of a spreadsheet, then a woman coding, and then a women designing a pie chart.

Monthly Reports

Cartoon of a spreadsheet, then a woman coding, and then a women designing a pie chart and finally a woman writing some notes.

Back to square one

The data was wrong - can you re-run the analysis?
Your manager loves it - can you do it for another region?
Next month - do it all again.

There must be a better way

Hello quarto 👋

What is quarto?

An open-source scientific and technical publishing system

A schematic representing the multi-language input (e.g. Python, R, Observable, Julia) and multi-format output (e.g. PDF, html, Word documents, and more) versatility of Quarto.

Artwork from “Hello, Quarto” keynote by Julia Lowndes and Mine Çetinkaya-Rundel, presented at RStudio Conference 2022. Illustrated by Allison Horst.

Example report

statsrhian.github.io/example-quarto-report/example-report.html

Template based-reports

#| code-line-numbers: "1-8|6-8|2-3"
---
title: "NHS Workforce Statistics for `r params$ics_name`"
subtitle: "Data for `r params$month_year`"
author: "Maria Garcia"
date: "2023-09-28"
params:
  ics_name: "North East and North Cumbria"
  month_year: "April 2023"
---

Interweave text and code 🧶

Read in the data

filename = glue("NHS Workforce Statistics, {params$month_year} England and Organisation.xlsx")

Clean the data

#| code-line-numbers: "3"
staff_group = 
  staff_group |>
  filter(`ICS name` == params$ics_name) |>
  select(`Organisation name`, `Total`,
         `HCHS Doctors`, `Nurses & health visitors`,
         `Midwives`, `Ambulance staff`)

Add insight

The table below shows the total number of doctors and nurses for each organisation within `r params$ics_name`. We can see that the organisation with the most midwives is the `r pull(max_midwives, "Organisation name")` with `r round(max_midwives$Midwives)` staff.

Re-run next month

#| code-line-numbers: "8"
---
title: "NHS Workforce Statistics for `r params$ics_name`"
subtitle: "Data for `r params$month_year`"
author: "Maria Garcia"
date: "2023-09-28"
params:
  ics_name: "North East and North Cumbria"
  month_year: "May 2023"

Report a different region

#| code-line-numbers: "7"
---
title: "NHS Workforce Statistics for `r params$ics_name`"
subtitle: "Data for `r params$month_year`"
author: "Maria Garcia"
date: "2023-09-28"
params:
  ics_name: "Lancashire and South Cumbria"
  month_year: "May 2023"

Maria is happy

More reproducible workflow
Fewer mistakes
Spends less time formatting the reports manually
Spends more time adding insight

Cartoon of a woman smiling